Hyperparameter Search: Adaptive (Simple)

The adaptive_simple searcher takes two intuitive configuration options capturing how many configurations to search and a maximum resource budget allowed per configuration:

• max_trials: The maximum number of hyperparameter configurations that will be explored. Most of these configurations will not be trained to convergence; rather, the search method will use early-stopping to prune hyperparameter configurations that are not performing well.

• max_steps: The maximum number of steps that any trial that survives to the end of the experiment will be trained for (a step is a fixed number of batches). This quantity is domain-specific and should roughly reflect the number of training steps needed for the model to converge on the data set. For users who would like to determine this number experimentally, train a model with reasonable hyperparameters using the single search method.